Toward Pre-empted EV Charging Recommendation Through V2V Based Reservation System

Cao, Yue; Tao, Jiang; Kaiwartya, O.; Sun, Hongjian; Zhou, Huan; Wang, Ran

Abstract

Electric vehicles (EVs) are being introduced by different manufacturers, thanks to their environment-friendly perspective to alleviate CO₂ pollution. In this paper, the proposed EV charging management scheme enables pre-empted charging service for heterogeneous EVs (depends on different charging capabilities, brands, etc.). Particularly, the anticipated EVs' charging reservations information, including their arrival time and expected charging time at charging stations (CSs), are brought for planning CS-selection (where to charge). Along with applying ubiquitous cellular network communication to deliver (delay tolerant) EVs' charging reservations, we further study the feasibility of applying opportunistic vehicle-to-vehicle (V2V) communication with delay/disruption tolerant networking (DTN) nature, due primarily to its flexibility and cost-efficiency in vehicular ad hoc networks (VANETs). Evaluation results under the realistic Helsinki city scenario show that applying the V2V-based charging reservation is promisingly cost-efficient in terms of communication overhead, while achieving a comparable charging performance to apply cellular network communication.

Citation

Cao, Y., Tao, J., Kaiwartya, O., Sun, H., Zhou, H., & Wang, R. (2021). Toward Pre-empted EV Charging Recommendation Through V2V Based Reservation System. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 51(5), 3026-3039. https://doi.org/10.1109/tsmc.2019.2917149

• Journal Article Type: Article
• Acceptance Date: Mar 13, 2019
• Online Publication Date: Jun 11, 2019
• Publication Date: 2021-05
• Deposit Date: Jun 25, 2019
• Publicly Available Date: Jun 27, 2019
• Journal: IEEE Transactions on Systems, Man, and Cybernetics: Systems.
• Print ISSN: 2168-2216
• Electronic ISSN: 2168-2232
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 51
• Issue: 5
• Pages: 3026-3039
• DOI: https://doi.org/10.1109/tsmc.2019.2917149
• Public URL: https://durham-repository.worktribe.com/output/1298799